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Lessons Learned from the TRANSED 2007 Conference

2007· article· en· W617024388 sur OpenAlexaboutno aff
Verónica Gil

Notice bibliographique

Revue23RD PIARC WORLD ROAD CONGRESS PARIS, 17-21 SEPTEMBER 2007 · 2007
Typearticle
Langueen
DomaineNeuroscience
ThématiqueTactile and Sensory Interactions
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésSignagePedestrianCountdownTransport engineeringPedestrian crossingContext (archaeology)VisibilitySchema crosswalkLegibilityComputer scienceTelecommunicationsEngineeringGeographyAdvertisingBusiness
DOInon disponible

Résumé

récupéré en direct d'OpenAlex

The 11th International Conference on Mobility and Transport for Elderly and Disabled Persons (TRANSED 2007) was held June 18-22, 2007, at the Palais des congres de Montreal under the theme Benchmarking, Evaluation and Vision for the Future. The infrastructure of these various modes of transportation, without which they could not be accessible, was one of the issues raised at this conference. The rapidly aging population in industrialized societies must be taken into account when planning infrastructure and facilities. Therefore, several sessions dealt specifically with pedestrian accessibility, readability and clarity of signage, road markings and lighting, in the context of international experience. The suggested improvements focused on slower pedestrians, such as seniors, and consisted of changes to road infrastructure to calm traffic (narrowing the road, refuge islands, changes to the surface of the road, speed bumps), improve pedestrian visibility (flashing green light, large visible signs indicating pedestrian crossings, etc.) and simplify and extend the crossing phases (e.g. pedestrian detectors). Finally, extending the sidewalks at intersections to the edge of the parking spaces was suggested to make it easier for pedestrians to see and be seen, as well as decrease crossing time. New safety-based designs for audible signals for people who are blind or visually impaired were presented. These include on-site or remote user activation, a push-button audible location device, tactile repeaters, and a melodic audio signal (rich in harmonics). Other details, such as alternating the audio signal on either side of the intersection and installing the equipment on the poles closest to the corners, would also help pedestrians head in the right direction before and while crossing. In addition, lowering the curb to make it more accessible to people with reduced mobility creates an obstacle for people with visual impairments by making it more difficult for them to feel where the curb is. To compensate, changes in surface texture (tiles with textured lines, texture stamped into cement, different types of domes, etc.) are used as reference points by blind pedestrians; research into the effectiveness and safety of warning tiles in the winter, as well as which tiles work best in these conditions, is ongoing. In order to make it possible to safely cross at intersections without audible signals, the development of automated systems to assist people who are blind, visually impaired, or have reduced mobility, using information already available in the infrastructure (Pedestrian Information and Communication Systems (PICS), Visible Light Communication (VLC)) is very promising. Research is also being conducted on systems that integrate several types of data (GPS, mapping accessible points, etc.) in order to determine the best itinerary to follow. It was also shown that it is important to make designers, contractors, and maintenance workers aware that they should not neglect elements such as access to and choice of accessible parking spaces, temporary or permanent barriers (news stands, benches, snow, garbage, etc.), and the location and design of bus stops and shelters, which can also be a major barrier for elderly and disabled persons. This conference reviewed international advances in transportation mobility infrastructure and will help implement future solutions that will promote independence for all. For the covering abstract see ITRD E139491.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesMéta-épidémiologie (sens strict), Charge utile insuffisante (le modèle a refusé de juger)
Catégories consensuellesCharge utile insuffisante (le modèle a refusé de juger)
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: Sans objet
GenreSignal candidat: Empirique · Signal consensuel: aucune
Score de désaccord entre enseignants0,650
Score d'incertitude au seuil1,000

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0000,000
Méta-épidémiologie (sens strict)0,0010,000
Méta-épidémiologie (sens large)0,0010,000
Bibliométrie0,0000,001
Études des sciences et des technologies0,0010,001
Communication savante0,0000,001
Science ouverte0,0010,000
Intégrité de la recherche0,0000,002
Charge utile insuffisante (le modèle a refusé de juger)0,0190,004

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,104
Tête enseignante GPT0,347
Écart entre enseignants0,243 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; les deux têtes enseignantes s’accordent sur ce qui est montré ici.

Devis d'étudeSans objet
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2007
Routes d'admission1
Résumé présentoui

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